Enabled by the digitization and digitalization of the business world, never before have companies had access to so much information. Every day, insights are gathered externally that can reveal how to better serve customers, how to partner more effectively, and how to source and deliver products more profitably. Internal information can reveal process inefficiencies, missed opportunities, hidden costs and other factors that directly impact the company’s short- and long-term financial success.

For the vast majority of businesses, managing this data and mining it for insights represent significant challenges. As the overall data volume has grown, IT budgets have been reduced — making it difficult to devote employee time and skill-sets to the task of data management. At best, many businesses are fulfilling their industry’s compliance and regulatory requirements, but not looking deeper into the strategic value of their stored information.

As a result, most companies have an overwhelming amount of trivial information that’s indistinguishable from valuable strategic insights. This “digital debris” stands in the way of effectively leveraging the truly important information that’s available. In a 2002 study, the Compliance, Governance and Oversight Council (CGOC) reported that 69 percent of the information retained by organizations has no current business or legal value. So then why is kept? A bit tongue-in-cheek, but no one has ever been fired for keeping data. The reality is that data stewardship also requires an effective data disposal process to continually cull the vast amounts of data seeking asylum in the data center that no longer has relevance to the business.

Automation: The Key to Leveraging Data

There is good news. Just as technology advancements have created today’s enormous data volume, technology can also help solve the practical problem of harnessing all this information as a competitive advantage. Clearly, the manual labor needed to gather, check, sort and sift through gigabytes of information is simply not available — and this approach would not be cost-effective in any case.

What’s needed to establish an intelligent data governance program are automated technology solutions that can help manage the three key tasks involved in data management:

Ensuring data quality

Making data identifiable

Centralizing data and making it accessible

Thankfully, intelligent software tools are available to address each one of these needs.

Ensuring Data Quality

Given the huge amount of irrelevant data that’s being stored by companies today, the first step is to cleanse all information and separate the important from the trivial. While there are many flaws in corporate data — typically caused by data-entry errors — a data governance program can identify and address these.

Once an organization has defined customized rules and policies around data quality, data governance software solutions can apply these across gigabytes of data in a relatively fast, automated manner. For example, an intelligent software-based policy engine can quickly delete all data that is past its appropriate retention deadline, or flag data that violates logical rules and is probably flawed.

Making Data Identifiable

An equally important task is making data easy to identify. The average business has a wealth of file types being stored — from audio and video files to Excel spreadsheets and Word docs. In order for employees to find what they’re looking for, quickly and easily, companies need to bring new structure to this mass of unstructured data.

By applying various data services rules and policies — again, via an automated solution — organizations can define how every file is described, see what it contains and understand its strategic value. Any employee with verified access can see all this information without the tedious job of opening every file.

As compliance and regulatory standards increase, unfortunately many businesses are being forced to store more data, for longer periods of time. By using an automated tool to tag all this stored information, companies can meet industry requirements while also identifying those files with high strategic value. Tagging a file is a form of classification or categorization whereby custom descriptors are stored with the file as metadata (which is a set of data that describes or gives information about other data – in this case, the file in question). Effective and complete metadata management both makes the data more identifiable and is essential before data is centralized and made accessible or mobile.

Centralizing Data and Making It Accessible

The next challenge is making sure data is centralized and can be easily accessed by those in the organization who need the information. Centralization does not mean data must reside in a single physical location. Instead, it means that all information must be shared, despite the functional boundaries and disparate sources that characterize most corporate information today.

Modern data centers, which are facilitated by intelligent software solutions, support flexibility and innovation by ensuring that cleansed, identifiable data is available across the organization. Technology tools also standardize data management practices, access policies, security protocols and compliance rules — all without the need for ongoing manual labor and constant human intervention.

Harnessing the Power of Information

In today’s digital age, nearly every business is overwhelmed with information, and challenged to leverage that data in a strategic manner.

By relying on automated solutions to cleanse, identify and centralize all this information, today’s leaders are creating a “single source of truth” that has enormous strategic value. These forward-looking companies have novel insights about their daily operations, their customers and trading partners, their finances and emerging market trends that are positioning them for success. Those who fail to harness the power of data within their own organizations are destined to fall behind.